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Traditional methods for evaluating decision-making provide valuable insights yet may fall short in capturing the complexity of this cognitive capacity, often providing insufficient for the multifaceted nature of decisions. The Kalliste Decision Task (KDT) is introduced as a comprehensive, ecologically valid tool aimed at bridging this gap, offering a holistic perspective on decision-making. In our study, 81 participants completed KDT alongside established tasks and questionnaires, including the Mixed Gamble Task (MGT), Iowa Gambling Task (IGT), and Stimulating & Instrumental Risk Questionnaire (S&IRQ). They also completed the User Satisfaction Evaluation Questionnaire (USEQ). The results showed excellent usability, with high USEQ scores, highlighting the user-friendliness of KDT. Importantly, KDT outcomes showed significant correlations with classical decision-making variables, shedding light on participants' risk attitudes (S&IRQ), rule-based decision-making (MGT), and performance in ambiguous contexts (IGT). Moreover, hierarchical clustering analysis of KDT scores categorized participants into three distinct profiles, revealing significant differences between them on classical measures. The findings highlight KDT as a valuable tool for assessing decision-making, addressing limitations of traditional methods, and offering a comprehensive, ecologically valid approach that aligns with the complexity and heterogeneity of real-world decision-making, advancing research and providing insights for understanding and assessing decision-making across multiple domains. [ABSTRACT FROM AUTHOR]

The three-way decision paradigm is a decision-making approach that is analogous to human reasoning. It involves a neutrosophic set as an efficient tool for handling ambiguity. Using cotangent similarity, the Hamming distance, and the innovative Vicis-Wave Hedges distance for ranking, this study proposes three novel three-way decision models based on the Bayes decision. In particular, single-valued neutrosophic numbers are employed to represent each loss function. The proposed models are then condensed into an algorithm. Subsequently, an example is presented to demonstrate the validity and rationality of the proposed models. Finally, we compare the three models. This research provides a new method for decision-making problems. [ABSTRACT FROM AUTHOR]

Many animals, including humans, must make decisions when outcomes involve risk and/or ambiguity. To explore the evolutionary roots of decision making when outcomes are unknown, we modified the Balloon Analogue Risk Task (BART) for use with tufted capuchin monkeys (Sapajus [Cebus] apella), creating the Primate Analogue Risk Task (PART). Using both the BART and the PART, we first compared human performance across the two tasks using analogous parameters. Humans' performance on the two tasks was positively correlated. Next, we tested capuchin monkeys' performance on the PART to assess their decision-making strategies in the context of ambiguity. Secondarily, although it was not the main goal of the study, this allowed us to look at species differences between capuchins' and humans' performance. Finally, we investigated the influence of prior experience on human and capuchin decision-making behavior. Neither capuchins nor humans behaved differently following an unsuccessful trial compared to a successful trial. We found individual differences in capuchin monkeys' choice behavior, though as a whole they demonstrated a pattern of reward maximization over time. Finally, as a species, capuchins had lower PART risk scores than humans. This paradigm presents a useful way to assess behavior in a context with uncertain outcomes using a comparative approach. [ABSTRACT FROM AUTHOR]

When deciding whether to reciprocate trust, people are typically strongly influenced by how much trust their interaction partner has originally shown them. If a partner has placed a lot of trust in you, there is a strong motivation to reciprocate, and indeed this factor often outweighs pro-self considerations to maximize one's own financial payout. However, one important unanswered question in this regard is what people decide to do when this prior information is ambiguous; that is, when they do not know for sure exactly how trusting their partner has been. How then do people decide to reciprocate? This study utilizes a novel version of the Trust Game to directly address this question. Here, we develop, and validate, a computational model-based approach to quantify and categorize how participants assessed the trustworthiness of an unfamiliar partner when making reciprocity decisions. We find that participants spontaneously use their prior experience about the trustingness of game partners in general to inform their reciprocity decisions, even when they had the opportunity to strategically assume that their new, unfamiliar, partners were untrusting, and hence could have justified lower reciprocation rates. [ABSTRACT FROM AUTHOR]

Uncertainty has long been of interest to economists and psychologists and has more recently gained attention among ecologists. In the ecological world, animals must regularly make decisions related to finding resources and avoiding threats. Here, we describe uncertainty as a perceptual phenomenon of decision‐makers, and we focus specifically on the functional ecology of such uncertainty regarding predation risk. Like all uncertainty, uncertainty about predation risk reflects informational limitations. When cues are available, they may be novel (i.e. unknown information), incomplete, unreliable, overly abundant and complex, or conflicting. We review recent studies that have used these informational limitations to induce uncertainty of predation risk. These studies have typically used either over‐responses to novelty (i.e. neophobia) or memory attenuation as proxies for measuring uncertainty. Because changes in the environment, particularly unpredictable changes, drive informational limitations, we describe studies assessing unpredictable variance in spatio‐temporal predation risk, intensity of predation risk, predator encounter rate, and predator diversity. We also highlight anthropogenic changes within habitats that are likely to have dramatic impacts on information availability and thus uncertainty in antipredator decisions in the modern world. [ABSTRACT FROM AUTHOR]

The extension of intuitionistic fuzzy sets (IFS) to Pythagorean fuzzy sets (PFS) is a significant advancement, addressing the inherent limitations of IFS. This study introduces a novel entropy measure specifically designed for Pythagorean fuzzy sets, establishing its axiomatic definition and presenting key properties. Decision making guided by entropy is advantageous, as it effectively mitigates ambiguity with increasing entropy values. Furthermore, a numerical example is provided to facilitate a comparative assessment of our newly introduced entropy measure in contrast to existing PFS entropy measures. The validation of our findings is achieved through the application of the COPRAS method, which determines decision outcomes based on a multitude of influencing factors. Notably, the determination of weights in this method is underpinned by the utilization of our innovative entropy measure. [ABSTRACT FROM AUTHOR]

Humans often face the challenge of making decisions between ambiguous options. The level of ambiguity in decision-making has been linked to activity in the parietal cortex, but its exact computational role remains elusive. To test the hypothesis that the parietal cortex plays a causal role in computing ambiguous probabilities, we conducted consecutive fMRI and TMS-EEG studies. We found that participants assigned unknown probabilities to objective probabilities, elevating the uncertainty of their decisions. Parietal cortex activity correlated with the objective degree of ambiguity and with a process that underestimates the uncertainty during decision-making. Conversely, the midcingulate cortex (MCC) encodes prediction errors and increases its connectivity with the parietal cortex during outcome processing. Disruption of the parietal activity increased the uncertainty evaluation of the options, decreasing cingulate cortex oscillations during outcome evaluation and lateral frontal oscillations related to value ambiguous probability. These results provide evidence for a causal role of the parietal cortex in computing uncertainty during ambiguous decisions made by humans. Humans often face the challenge of making decisions between ambiguous options. The level of ambiguity in decision-making has been linked to activity in the parietal cortex, but what is its actual role? This study uses fMRI and TMS-EEG to show that the parietal cortex is causally involved in a computational processes that underestimate uncertainty during decision-making under ambiguity. [ABSTRACT FROM AUTHOR]

Nursing education and training in Ecuador presents a complex and multifaceted situation, marked by ambiguities, inconsistencies, and contradictions in pedagogical and curricular approaches. In this context, the general objective of this neutrosophic analysis was to identify and understand these ambiguities, inconsistencies, and contradictions, while seeking solutions and improvements from a neutrosophic perspective. The results of this research revealed that the variable "relevance of curricular updating" is fundamental and that factors such as updating, relevance, implementation, and continuous evaluation interact in a complex way. Neutrosophic statistics provided precise data on their relative influence. In summary, it is concluded that addressing ambiguities and contradictions in nursing education and training in Ecuador requires continuous evaluation, collaboration between institutions, curricular flexibility, and feedback from multiple stakeholders. This neutrosophic approach is essential to make informed decisions and improve the quality of nursing education in the country. [ABSTRACT FROM AUTHOR]

In this article, we have proposed an ordering technique for Neutrosophic numbers with non-linear functions. Consequently, the non-linear functions overcome the limitations of linear function approaches by giving an enhanced framework for handling and modeling uncertainty. Hence, this study presents the Generalized Parabolic Single Valued Neutrosophic Number (GPSVNN) to address the uncertainties in Multi-Criteria Decision-Making (MCDM) circumstances. GPSVNN can handle uncertainty and perform arithmetic operations to deal with MCDM through the (α, β, γ)-cut technique. The computation of the (α, β, γ)-cut of the neutrosophic number is reduced by defining the "value" and "ambiguity." As a result, it becomes more systematic when the complicated computations using the (α, β, γ)-cut approach are carried out. A novel ordering approach has been developed in this study by incorporating the "value" and "ambiguity" of GPSVNN. Finally, we have given an example using GPSVNN in a life satisfaction survey to show its applicability. [ABSTRACT FROM AUTHOR]

The interval complex single-valued neutrosophic hypersoft set (Ξ-set), together with its features and set-theoretic operations, is a new mathematical structure that is discussed in this article. For managing ambiguous and uncertain knowledge, the suggested structure integrates the interval complex single-valued neutrosophic set and hypersoft set. These two elements have already been regarded as trustworthy settings. The first component has the ability to manage information on interval and periodic types, while the second offers a multi-argument domain for concurrent consideration of numerous sub-attributes. The Ξ-set is used to aggregate these sets, allowing for the fusion of various qualities and any related uncertainty. The resultant aggregated sets, which take into account both the attribute values and the associated uncertainty, give a thorough representation of the decision aspect. To assist in decision-making, the method calculates how similar several options are to the optimum option using a distance-based similarity metric. By contrasting the combined sets of several options, the system determines the best option based on the specified selection criteria. Decision-makers can evaluate how changing attribute values may influence their choices using the suggested strategy’s endorsement of sensitivity analysis. The efficacy of the recommended decision-support mechanism is demonstrated through a case study with a real-world choice dilemma. The results show how well the framework can handle ambiguity and uncertainty while providing decision-makers with meaningful insights and encouraging rational choices. Finally, the multi-attribute decision-support system based on aggregations of Ξ-set provides a reliable framework for dealing with difficult choice issues that are characterized by ambiguity and vagueness. [ABSTRACT FROM AUTHOR]

The dual-process theory of career decision-making (DTC; Xu, 2021a ; 2021b) resulted from a synthesized and critical reflection of career decision-making and related models in the contemporary psychosocial context of career development. The DTC features persistent decision uncertainty as a salient condition of contemporary career decision-making, and its theoretical framework and predictive model establish DTC's conceptual and empirical foundation, respectively. However, the DTC and the career decision-making literature in general still lack a process-oriented prescriptive model that foregrounds decision uncertainty. Consequently, the extant literature fails to prescribe key decision-making components and procedures under decision uncertainty. Thus, drawing on the DTC, decision-making science, and existing models of career decision-making, we propose a four-stage process model, which involves four interlinked macro stages and micro steps within each stage. The model also involves five propositions to explain and predict the effects of important personal and environmental factors on the process and outcomes of each stage. We describe the DTC process model and use a case example to illustrate how the model can be applied in practice. Together, the DTC's theoretical framework, predictive model, and process-oriented prescriptive model constitute a comprehensive theory regarding dynamic career decision-making and adaption in an uncertain world and offer diverse research and practical implications. [ABSTRACT FROM AUTHOR]

A major concern with Bayesian decision making under uncertainty is the use of a single probability measure to quantify all relevant uncertainty. This paper studies prior robustness as a form of continuity of the value of a decision problem. I show that this notion of robustness is characterized by a form of stable choice over a sequence of perturbed decision problems, in which the available acts are perturbed in a precise fashion. I then introduce a choice-based measure of prior robustness and apply it to models of climate mitigation and portfolio choice. • Belief Robustness and Continuity: Beliefs are "robust" if minor changes in beliefs lead to minor changes in choices. This notion can be tested by evaluating perturbations of feasible bets. • Measure of Robustness: A comparative measure of belief robustness can quantify the sensitivity of optimal choices to parametric assumptions. • Impact on Key Economic Models: The measure shows that heavy-tailed distributions yield more robust choices in portfolio and economy-climate models, highlighting its practical importance. [ABSTRACT FROM AUTHOR]

Leaders face increasingly complex challenges, prompting a renewed focus on engaging stakeholders in organizational change processes. Traditional approaches to change, relying on external experts, have been unsatisfactory and leaders are seeking new methods that address the shortcomings. The Dialogic OD mindset, which involves giving stakeholders significant influence over change, has proven to be more effective in producing rapid, transformational change, but leaders often resist using these approaches. Generative change strategies, such as emergent strategy, co-design, open space, among many, emphasize trying things out and learning as you go, which contradicts the preference for certainty and predictability among managers. Generative leadership challenges the belief that leaders have all the answers and instead invites others to make decisions and self-initiate action. Leaders may feel uncomfortable and unsure of their role in leading generative change processes and need coaching and support. To prepare leaders to hold generative spaces, we offer a "a three-legged stool' for OD consultants and coaches to better support leaders before dialogic events: conceptual alignment, embodied self-scaffolding, and contracting the "what ifs." [ABSTRACT FROM AUTHOR]

The dual-process theory of career decision-making (DTC) adds to the conversation about understanding and facilitating career decision-making from a more realistic and inclusive perspective and highlights the joint operation of decision ambiguity and ambiguity management strategies in career decision-making. However, a psychometrically sound measure of decision ambiguity is lacking. Thus, the current study used two samples of U.S. college students to develop and initially validate a measure of decision ambiguity (CDMA). Study 1 (n = 195) developed the CDMA and found initial evidence for a unidimensional structure. Study 2 (n = 271) cross-validated the unidimensional structure of the CDMA and supported the convergent, discriminant, concurrent, and incremental validities of the CDMA. Specifically, the results supported (1) the differential associations of the CDMA with need for information and with neuroticism/negative affectivity, lack of readiness, and interpersonal conflicts, (2) the positive association between the CDMA and choice/commitment anxiety, and (3) the incremental predictions of the CDMA for career decidedness, career certainty, and major satisfaction over and beyond need for information. Therefore, the current study offers a psychometrically sound measure of decision ambiguity, which has potential to facilitate the scientific inquiry and social justice application of the DTC. [ABSTRACT FROM AUTHOR]

The uncertainty and ambiguity in information is the major problem to aggregate. Some fuzzy frameworks and aggregation operators (AOs) have been formalized to cope with the uncertainty in information. A framework known as a spherical fuzzy set (SFS) covers the maximum possible information from real-life scenarios. Hence, the use of the SFS in multi-attribute decision-making (DM) (MADM) is very significant. This article consists of the development of some new AOs for the framework of the SFS. A family of the AOs spherical fuzzy Schweizer-Sklar (SS) McLaurin symmetric mean (MSM) (SFSSMSM), spherical fuzzy SS weighted MSM (SFSSWMSM), spherical fuzzy SS dual MSM (SFSSDMSM), and spherical fuzzy SS dual weighted MSM (PFSSDWMSM) is introduced, and their basic properties are investigated. The developed AOs are applied to the MADM problem where some pilot health projects (PHP) are assessed. [ABSTRACT FROM AUTHOR]

Uncertainty is prevalent in various health contexts. It is imperative to understand how health-related uncertainty can impact individuals' healthcare experiences and health decision making. The purpose of the present paper is to provide five overarching recommendations from an interdisciplinary team of experts to address gaps in the literature on health-related uncertainty. We present a case study of health-related uncertainty within the specific context of alcohol use to demonstrate these gaps and provide context for the recommendations. The five recommendations concerning health-related uncertainty include: (1) use common, consistent terminology to discuss uncertainty, (2) clarify measures of individual differences in response to uncertainty, (3) increase research on uncertainty and affect, (4) investigate the impact of the channel through which uncertainty is communicated, and (5) develop theory-driven interventions to improve uncertainty management. We conclude by reviewing health contexts in which health-related uncertainty exists and note how our recommendations complement existing reviews and data. [ABSTRACT FROM AUTHOR]

Risk and uncertainty are central concepts of decision neuroscience. However, a comprehensive review of the literature shows that most studies define risk and uncertainty in an unclear fashion or use both terms interchangeably, which hinders the integration of the existing findings. We suggest uncertainty as an umbrella term that comprises scenarios characterized by outcome variance where relevant information about the type and likelihood of outcomes may be somewhat unavailable (ambiguity) and scenarios where the likelihood of outcomes is known (risk). These conceptual issues are problematic for studies on the temporal neurodynamics of decision-making under risk and ambiguity, because they lead to heterogeneity in task design and the interpretation of the results. To assess this problem, we conducted a state-of-the-art review of ERP studies on risk and ambiguity in decision-making. By employing the above definitions to 16 reviewed studies, our results suggest that: (a) research has focused more on risk than ambiguity processing; (b) studies assessing decision-making under risk often implemented descriptive-based paradigms, whereas studies assessing ambiguity processing equally implemented descriptive- and experience-based tasks; (c) descriptive-based studies link risk processing to increased frontal negativities (e.g., N2, N400) and both risk and ambiguity to reduced parietal positivities (e.g., P2, P3); (d) experience-based studies link risk to increased P3 amplitudes and ambiguity to increased frontal negativities and the LPC component; (e) both risk and ambiguity processing seem to be related with cognitive control, conflict monitoring, and increased cognitive demand; (f) further research and improved tasks are needed to dissociate risk and ambiguity processing. [ABSTRACT FROM AUTHOR]

Decision-makers often are faced with uncertain situations in which they have incomplete information. While risky decisions include the probabilities of the possible outcomes, ambiguous decisions involve both unknown probabilities and unknown outcomes. Prior research has suggested that there are differences in how men and women evaluate risk, but evidence related to gender and ambiguity is mixed. The present work approaches this problem from a novel angle, focusing on the use of information that is present rather than the impact of information that is absent. It examines how individuals assign value in uncertain decisions based on the partial information they do have. While a main effect of gender on value is not observed, there is an enhanced "optimism bias" in how both favorable and unfavorable information influences the subjective value of ambiguous financial prospects for male compared to female participants. Unpacking these effects suggests multiple mechanisms, including a significant contribution of risk processing. Specifically, favorable and unfavorable information are over- and underweighted respectively in male participants' estimated likelihood of a winning outcome, and unfavorable information is underweighted in estimating certainty. There also is an interaction of gender and risk preferences, such that value increases more for male participants as the subjectively estimated likelihood of winning increases. A second experiment demonstrates this risk interaction effect is also observed for objective probabilities of winning, suggesting that the relationship between value and risk uses similar mechanisms across layers of uncertainty. [ABSTRACT FROM AUTHOR]

Adolescence is a period of development in which youth have new opportunities for decision-making, often in situations where they may have little information or experience to guide their choices. Thus, learning to make decisions under uncertainty is a key challenge during adolescence. To date, researchers have applied economics formalisms to understand the processes that support adolescents in making decisions under two distinct forms of uncertainty: economic risk and economic ambiguity. Economic risk is when the probabilities of outcomes are known. Economic ambiguity is when the probabilities of outcomes are unknown or unknowable. This research has led to foundational knowledge about the basic processes involved in adolescent decision-making, but many experimental paradigms that dissociate economic risk and ambiguity rely on monetary or point-based choices. Given that adolescence is a period of development characterized by a changing social environment, it remains unclear whether the processes that adolescents engage during decision-making on monetary or point-based experimental tasks generalize to their day-to-day experiences in the real world. In this brief piece, we explore how developmental research applying economics formalisms can be bolstered by research on youth's social environments to advance our understanding of decision-making in adolescence. First, we review developmental research by using economic uncertainty paradigms. Next, we highlight research on adolescents' social environments to provide examples of the day-to-day choices that adolescents face among their peers and in their broader communities. Finally, we propose directions for future research integrating these separate approaches to create a more nuanced, ecologically informed understanding of adolescent decision-making. [ABSTRACT FROM AUTHOR]

Theories of behaviour, choice, and action have long presented an "act" as a kind of bottleneck of meaning‐making, where the action is either a cocktail of partial preferences or the survival of one over the rest. I argue that action is often something very (if subtly) different and propose "ambivalent action" as a category of moral action defined by the actor's conflicting intentions, in which the conflict is reified (not resolved) by the act. Situated in past and contemporary context, the term is an interdisciplinary bridge, with links from classical (if vague) theoretic treatments of "ambivalence" to new sociological analogies in the realm of quantum physics. I explore this duality through the case study of #BlackoutTuesday, a social media movement connected with global protests against police brutality and racism. The black square that characterized the movement is best understood as ambivalent action, as an act of two‐fold narrative‐making: "both" silence and speech. The "success" of an ambivalent action in remaining in two narratives at once is determined by the audience. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is a major health and socio-economic problem since it is one of the major sources of death and disability worldwide. TBI patients usually show high heterogeneity in their clinical features, including both cognitive and emotional/behavioral alterations. As it specifically concerns cognitive functioning, these patients usually show decision-making (DM) deficits. DM is commonly considered a complex and multistep process that is strictly linked to both hot and cold executive functioning and is pivotal for daily life functioning and patients' autonomy. However, the results are not always in agreement, with some studies that report huge alterations in the DM processes, while others do not. The present systematic review and meta-analysis aims to integrate past literature on this topic, providing a clear and handy picture both for researchers and clinicians. Thirteen studies addressing domain-general DM abilities were included from an initial N = 968 (from three databases). Results showed low heterogeneity between the studies (I2 = 7.90, Q (12) = 13.03, p =.37) supporting the fact that, overall, TBI patients showed lower performance in DM tasks as compared to healthy controls (k = 899, g =.48, 95% CI [0.33; 0.62]) both in tasks under ambiguity and under risk. The evidence that emerged from this meta-analysis denotes a clear deficit of DM abilities in TBI patients. However, DM tasks seemed to have good sensitivity but low specificity. A detailed description of patients' performances and the role of both bottom-up, hot executive functions and top-down control functions have been further discussed. Finally, future directions and practical implications for both researchers and clinicians have been put forward. [ABSTRACT FROM AUTHOR]

Privacy policies are critical for helping individuals make decisions on the usage of information systems. However, as a common language phenomenon, ambiguity occurs pervasively in privacy policies and largely impedes their usefulness. The existing research focuses on the identification of individual vague words or sentences, without considering the context of documents, which may cause a significant amount of false vagueness. Our goal is to automatically detect the potential false vagueness and the related supporting evidence, which illustrates or explains the vagueness, and therefore probably assist in alleviating the vagueness. We firstly analyze the public manual annotations and define four common patterns of false vagueness and three types of supporting evidence. Then we propose the approach of the F·vague-Detector to automatically detect the supporting evidence and then locate the corresponding potential false vagueness. According to our analysis, about 29–39% of individual vague sentences have at least one clarifying sentence in the documents, and experiments show good performance of our approach, with recall of 66.98–67.95%, precision of 70.59–94.85%, and F 1 of 69.24–78.51% on the potential false vagueness detection. Detecting the vagueness of isolated sentences without considering their context within the whole document would bring about one-third potential false vagueness, and our approach can detect this potential false vagueness and the alleviating evidence effectively. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the effects of Information Theory measures on the processing of polysemous nouns and reveal that the sensitivity to multiple related senses can be learned from the linguistic context. We collected large-scale data and applied a correlation design to show that an increase in sense uncertainty (or sense diversity) is followed by a faster visual lexical decision. The facilitatory effect of sense uncertainty was revealed by the predictive power of entropy, followed by the additional analysis, which revealed that both the number of senses and the balance of sense probabilities affected processing. For the first time, the balance of sense probabilities was described via redundancy to demonstrate the effect of the numerical description of the balance of sense probabilities. Finally, we crossed distribution semantics and discrimination learning to show that polysemy effects can arise as a consequence of the principles of error-driven learning. [ABSTRACT FROM AUTHOR]

While research has identified a five-factor model of career decision-making difficulty based on meta-analytical evidence and cross-cultural comparison, the field lacks an elaborated theoretical account of the joint operation of the five decision difficulties. The current study drew on the dual-process theory of career decision-making (DTC) to examine the interplay of the five decision difficulties in predicting career decidedness in the Chinese context. Study 1 developed and validated measures of decision ambiguity, advance in narrowing down, and career decidedness in a sample of Chinese college students (n = 180). Study 2 examined the structural model using another sample of Chinese college students (n = 408). Focusing on the relations of the five major decision difficulties to career decidedness, the results did not support the standalone mechanism of confusion management but supported the standalone mechanism of ambiguity management. Additionally, the results supported the crossover mechanism from confusion management to ambiguity management and the crossover mechanism from ambiguity management to confusion management. The results not only shed light on the role of each difficulty but also offer evidence for the interplay of key DTC macro elements. The practical implications based on the joint operation of the five decision-making difficulties are discussed. [ABSTRACT FROM AUTHOR]

In Roger Pielke Jr.'s The Honest Broker (2007) he discusses different roles a scientist can adopt when giving advice to policymakers. The honest broker role focuses on clarifying and expanding the scope of choice for others. This role has the virtues of being sensitive to known problems with experts being partisan by stealth, dominating policy decisions by controlling knowledge input, and reducing the scope of considerations deemed relevant to decision-making. Yet I argue that to the extent the honest broker role involves expanding the scope of choice, an array of problems arises. These include ambiguity about which and whose consensus ought to guide scientists in their decisions about what role to adopt, an implicit tendency to insulate politics from science, and a possible replication of the anti-pluralism of political populism. Drawing upon Phillip Pettit's critique of Isaiah Berlin's account of freedom as non-interference, I argue that the honest broker role for scientists inherits the problems afflicting accounts of freedom as the non-restriction of options: namely, the problems of adaptive preference formation and ingratiation. On this basis I suggest not advising scientists to be honest brokers, because doing so might fail to help them be reflexive scientists. [ABSTRACT FROM AUTHOR]

Uncertainty can be fractioned into risk and ambiguity psychologically and neurobiologically. However, whether and how risk and ambiguity are dissociated in terms of neural dynamics during value‐based decision making remain elusive. The present event‐related potential (ERP) study addressed these issues by asking participants to perform a wheel‐of‐fortune task either during a risky context (Experiment 1; N = 30) where outcome probability was known or during an ambiguous context (Experiment 2; N = 30) where outcome probability was unknown. Results revealed that the cue‐P3 was more enhanced for risk versus ambiguity during the anticipatory phase, whereas the RewP was more increased for ambiguity than risk during the consummatory phase. Moreover, the SPN and the fb‐P3 components were further modulated by the levels of risk and ambiguity, respectively. These findings demonstrate a neural dissociation between risk and ambiguity, which unfolds from the anticipatory phase to the consummatory phase. Our findings add a new perspective on neural dissociation between risk and ambiguity during value‐based decision making. We provide evidence that risk processing is associated uniquely with anticipatory ERPs, whereas ambiguity processing is more associated with consummatory ERPs. Our results highlight the multi‐phase nature of neural dissociation between risk and ambiguity. [ABSTRACT FROM AUTHOR]

In the article "What are neural correlates neural correlates of?" published in the journal BioSocieties, Gabriel Abend points out that neuroscientists cannot avoid philosophical questions concerning the conceptualization and operationalization of social-psychological phenomena they deal with at the physiological level. In this article, we build on Abend's thesis and, through a systematic literature review of decision neuroscience studies, test it with the example of the social-psychological phenomenon of uncertainty in decision making. In this paper, we provide an overview of studies that appropriately attempt to conceptualise uncertainty, and then use these studies to analyse papers looking for neural correlates of uncertainty. Based on a systematic review of studies, we investigate what types of uncertainty authors in the field of decision neuroscience address and define, what criteria they use to distinguish between these types, what problems are associated with their conceptualization, and whether the neural correlates of different types of uncertainty can be accurately identified. The paper concludes that, particularly in the economic context, a collaboration between the natural and social sciences works well, and neuroscience studies use economic conceptualizations of uncertainty that are further developed by sophisticated decision tasks. However, the paper also highlights problematic aspects that obscure the understanding of the phenomena under study. These include the lack of criteria for distinguishing between different types of phenomena, the unclear use of the general concept of uncertainty, and the confusion of phenomena or their erroneous synonymous use. [ABSTRACT FROM AUTHOR]

The control of spreading of COVID-19 in emergency situation the entire world is a challenge, and therefore, the aim of this study was to propose a spherical intelligent fuzzy decision model for control and diagnosis of COVID-19. The emergency event is known to have aspects of short time and data, harmfulness, and ambiguity, and policy makers are often rationally bounded under uncertainty and threat. There are some classic approaches for representing and explaining the complexity and vagueness of the information. The effective tool to describe and reduce the uncertainty in data information is fuzzy set and their extension. Therefore, we used fuzzy logic to develop fuzzy mathematical model for control of transmission and spreading of COVID19. The fuzzy control of early transmission and spreading of coronavirus by fuzzy mathematical model will be very effective. The proposed research work is on fuzzy mathematical model of intelligent decision systems under the spherical fuzzy information. In the proposed work, we will develop a newly and generalized technique for COVID19 based on the technique for order of preference by similarity to ideal solution (TOPSIS) and complex proportional assessment (COPRAS) methods under spherical fuzzy environment. Finally, an illustrative the emergency situation of COVID-19 is given for demonstrating the effectiveness of the suggested method, along with a sensitivity analysis and comparative analysis, showing the feasibility and reliability of its results. [ABSTRACT FROM AUTHOR]

Sexual consent is advocated around the world to reduce sexual assault. The widespread affirmative consent model emphasizes a need for unambiguous consent. In this paper, we contribute to a deeper understanding of how ambiguities in the initiations of sexual activities are routinely solved to achieve consent. Drawing on conversation analytic research on joint decision-making, and a dataset of 80 cases of sexual initiation in contemporary TV-series and movies, we investigate the interactional practices by which sexual activities are presented as consensual and how consent is achieved across sequences of interaction. We found there to be social advantages of synchronous initiation, compared to sequential verbal initiations, which were associated with various social vulnerabilities. These vulnerabilities could however be circumvented by two practices, each of which made use of a distinct combination of verbal and embodied resources. While ambiguities exist, our results oppose the idea of sexual consent as a practically hopeless and awkward endeavor. Instead, consent consists of joint action that is achieved through recognizable and systematic ways. [ABSTRACT FROM AUTHOR]

The degree of ambiguity (respectively, the path size) of a nondeterministic automaton, on a given input, measures the number of accepting computations (respectively, the number of all computations). It is known that deciding the finiteness of the degree of ambiguity of a nondeterministic pushdown automaton is undecidable. Also, it is undecidable for a given k ≥ 3 to decide whether the path size of a nondeterministic pushdown automaton is bounded by k. As the main result, we show that deciding the finiteness of the path size of a nondeterministic pushdown automaton can be done in polynomial time. Also, we show that the k -path problem for nondeterministic input-driven pushdown automata (respectively, for nondeterministic finite automata) is complete for exponential time (respectively, complete for polynomial space). • We show that finiteness of path size of nondeterministic pushdown automata can be solved in polynomial time. • We show that deciding k-path property is PSPACE complete for nondeterministic finite automata. • We show that deciding k-path property is exponential time complete for nondeterministic input-driven pushdown automata. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the attribute weights and decision-makers’ weights were unknown in the emergency decision-making process of public health emergencies, this paper proposed a Pythagorean fuzzy reductive BM operator decision-making method based on DEMATEL and trust network, which took into account the subjective and objective relationships to ensure the integrity of the emergency assessment system. Firstly, considering the important influence of key factors on the emergency decision-making of public health emergencies, it identified and determined attribute weights by the DEMATEL method, and taking the complex and diverse backgrounds of emergency decision-making as the entry point, it used the trust propagation path to improve the trust relationship and built a hybrid trust network that integrated the initial trust degree and preference similarity to obtain decision-makers’ weights. Secondly, considering the strong correlation between the properties of the emergency assessment, it introduced a Pythagorean fuzzy reductive BM operator based on the improved similarity measure and score function, and calculated the comprehensive evaluation value and the ranking of the plan. Finally, this paper applied the method to the emergency management assessment of sporadic cases in hospitals during the normalization of epidemic prevention and control period. It verifies the reliability and reasonable effectiveness of the method. [ABSTRACT FROM AUTHOR]

Tooth decay is a common problem among people due to many factors, including neglect to clean teeth. Dental caries is becoming more common in a number of countries worldwide. This study aims to determine the prevalence of dental caries and how to treat this problem. We also implement fuzzy soft multifunction between fuzzy soft topological spaces which is Smarandache's generation of the notion. In this paper, we generated additional topologies for an information system based on a similarity relation. This paper discussed two methods for determining accuracy: our method and Pawlak's qualitative data method. Both ideas show that because of the uncertainty and ambiguity of qualitative data, we get a lot of topologies based on one or two attributes. The new method was used to determine the accuracies. This method revealed the difference between one or two attributes. In fact, the most important factors affecting tooth decay have been identified. Furthermore, we are developing a new algorithm to treat dental caries problems. Tooth decay which includes the conclusions of some well-known results in the corresponding literature is highlighted and discussed. In addition, a comparative application that dwells on the generality of our obtained results is constructed. Our proposed approach is reasonable and effective. [ABSTRACT FROM AUTHOR]

Cubic Pythagorean fuzzy (CPF) set (CPFS) is a hybrid set that can describe both interval-valued Pythagorean fuzzy (IVPF) sets (IVPFSs) and Pythagorean fuzzy (PF) sets (PFSs) simultaneously for addressing information ambiguities. Since an aggregation operator (AO) is a significant mathematical approach in decision-making (DM) problems, this article presents some novel Bonferroni mean (BM) and weighted Bonferroni mean averaging operators between CPF-numbers (CPFNs) for aggregating the different preferences of the decision-makers. Then, using the proposed AOs, we develop a DM approach under the CPF environment and demonstrated it with a numerical example. Furthermore, a comparative study between the proposed and existing methods has been performed to demonstrate the practicality and efficiency of the proposed DM approach. [ABSTRACT FROM AUTHOR]

Rule-based classifiers use a collection of high-quality rules to classify new data instances. They can be categorized according to the adopted classification strategy: Classifiers based on a single rule, and classifiers based on multiple rules. Many works were proposed in this field. However, most of them do not handle imperfect data. In this study, we focus on the issue of multi-rules-based classification for evidential data, i.e., data where imperfection is modeled via the belief functions theory. In this respect, we introduce a new algorithm called PWEviRC. This latter involves a two-level pruning technique to remove redundant and noisy rules. Finally, it applies the Dempster rule of combination to fuse the selected rules and make the final decision. To evaluate the proposed method, we carried out extensive experiments on several benchmark data sets. The performance study showed interesting results in comparison to existing methods. [ABSTRACT FROM AUTHOR]

Decision making (DM) has a pivotal role in supporting individual autonomy and well-being. It is considered a complex ability exploiting many cognitive functions, among which executive functions (EFs) are crucial. Few studies analyzed the role played by EFs in DM in healthy adults under ambiguity and risk, which are common conditions for most decisions in daily life. This scoping review aims to analyze the relationships between two individual tasks widely used to assess DM under these conditions (Iowa Gambling Task and Game of Dice Task) and EFs. According to the organizing principle that conceptualizes hot and cold EFs, DM under such conditions mainly implies hot EFs, but the relationship with cold EFs is still unclear. Using such an approach, a comprehensive framework is provided, highlighting main findings and identifying possible gaps in the literature. The results suggest different roles played by cold EFs in DM under ambiguity and risk, according to the characteristics of the tasks. The findings can offer guidance to further studies and to design interventions to support DM in healthy adults. [ABSTRACT FROM AUTHOR]

This study expands on Keiser and Arthur's (2021) meta-analysis of the after-action review (AAR), or debrief, by examining six additional task and training characteristics that contribute to or attenuate its effectiveness. The findings based on a bare-bones meta-analysis of results from 83 studies (134 ds [955 teams; 4,684 individuals]) indicate that the effectiveness of the AAR (overall d = 0.92) does indeed vary across the pertinent characteristics. The primary impact of this study pertains to the practical implementation of AARs; notably, the findings indicate that the AAR is particularly effective in task environments that are characterized by a combination of high complexity and ambiguity in terms of offering no intrinsic feedback. The types of tasks—often project and decision-making—that more commonly entail these characteristics are frequently used in industries that do not traditionally use the AAR. The results also suggest that more recent variants of the AAR (i.e., a reaction phase, a canned performance review) do not meaningfully add to its effectiveness. These findings are combined with those from prior meta-analyses to derive 11 empirically-based practical guidelines for the use of AARs. In sum, this study highlights the complexity of the AAR that results from the independent and interdependent influence among various components and characteristics, the examination of the effects of novel and ostensibly distinct variants or approaches to AARs, and the extension of AARs to tasks and contexts in which they are less commonly used. [ABSTRACT FROM AUTHOR]

Charities differ, among other things, alongside the likelihood that their interventions succeed and produce the desired outcomes and alongside the extent that such likelihood can even be articulated numerically. In this paper, we investigate what best explains charitable giving behaviour regarding charities that have interventions that will succeed with a quantifiable and high probability (sure-thing charities) and charities that have interventions that only have a small and hard to quantify probability of bringing about the desired end (probabilistic charities). We study individual differences in risk/ambiguity attitudes, empathy, numeracy, optimism, and donor type (warm glow vs. pure altruistic donor type) as potential predictors of this choice. We conduct a money incentivised, pre-registered experiment on Prolific on a representative UK sample (n = 1,506) to investigate participant choices (i) between these two types of charities and (ii) about one randomly selected charity. Overall, we find little to no evidence that individual differences predict choices regarding decisions about sure-thing and probabilistic charities, with the exception that a purely altruistic donor type predicts donations to probabilistic charities when participants were presented with a randomly selected charity in (ii). Conducting exploratory equivalence tests, we find that the data provide robust evidence in favour of the absence of an effect (or a negligibly small effect) where we fail to reject the null. This is corroborated by exploratory Bayesian analyses. We take this paper to be contributing to the literature on charitable giving via this comprehensive null-result in pursuit of contributing to a cumulative science. [ABSTRACT FROM AUTHOR]

In multiple attribute decision making (MADM) issues, the ambiguity, imprecision, and imperfection of assessment information may lead to inadequate decision-making results. However, the Z-number suggested by Zadeh in 2011 could somehow prevent this problem. For MADM issues with unknown attributes weights, an extended Distance from the Average Solution (EDAS) method is proposed under a mixture Z-number environment. In addition, the Criteria Importance Through Inter-criteria Correlation (CRITIC) method is used to estimate the weights of the criterion, which is easy to calculate and avoids subjective forecasts. A novel illustrative example is provided to demonstrate the feasibility, validity, and practicability of the presented method, and is compared with existing decision methods. The outcome indicates that the suggested method can solve complicated decision-making problems. [ABSTRACT FROM AUTHOR]

Multi-criteria group decision-making (MCGDM) problems are fundamentally characterized by uncertainty and ambiguity. The quantification of such data is vital for determining the most optimal course of action. In this paper, a double-layer possibility degree-based interval-valued q-rung orthopair fuzzy sets (IV q -ROFSs) Vlsekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) approach is presented. First, the possibility degrees of IV q -ROFSs are calculated and processed to establish a new neutralized decision matrix. Second, the components of the new decision matrix are taken into account for obtaining a new pair of positive and negative ideal solutions. The utility and regret measures in the VIKOR approach are ultimately determined by combining criteria weights and cumulative possibility degrees to rank the alternatives. The results of the study show that the proposed approach contributes to acquiring accurate alternative rankings in situations where traditional approaches have had difficulty generating ranks. Also, by eliminating the early normalization stage, which has a direct impact on the final ranking, the proposed approach concludes a unique ranking for each decision-making problem. Several comparative and sensitivity analysis are also conducted to exhibit robustness and applicability of the proposed approach in real world. • A novel VIKOR approach is proposed based on possibility degrees of IV q -ROFSs. • A neutralized decision matrix is constructed based on cumulative possibility degrees. • A double-layer VIKOR is proposed to consider more imprecision of linguistic data. • Normalization step of linguistic data is eliminated for the neutralized decision matrix. • A construction material selection case is explored by using the proposed approach. [ABSTRACT FROM AUTHOR]

Urban planning is simultaneously shaped by and creates new (spatial) knowledge. The changes in planning culture that have taken place in the last decades--especially the so-called communicative turn in planning in the 1990s--have brought about an increased attention to a growing range of stakeholders of urban development, their interests, logics, and participation in planning as well as the negotiation processes between these stakeholders. However, while this has also been researched in breadth and depth, only scant attention has been paid to the knowledge (claims) of these stakeholders. In planning practice, knowledge, implicit and explicit, has been a highly relevant topic for quite some time: It is discussed how local knowledge can inform urban planning, how experimental knowledge on urban development can be generated in living labs, and what infrastructures can process "big data' and make it usable for planning, to name a few examples. With the thematic issue on "Spatial Knowledge and Urban Planning' we invited articles aiming at exploring the diverse understandings of (spatial) knowledge, and how knowledge influences planning and how planning itself constitutes processes of knowledge generation. The editorial gives a brief introduction to the general topic. Subsequently, abstracts of all articles illustrate what contents the issue has to offer and the specific contribution of each text is carved out. In the conclusion, common and recurring themes as well as remaining gaps and open questions at the interface of spatial knowledge and urban planning are discussed. [ABSTRACT FROM AUTHOR]

The Pythagorean fuzzy sets conveniently capture unreliable, ambiguous, and uncertain information, especially in problems involving multiple and opposing criteria. Pythagorean fuzzy sets are one of the popular generalizations of the intuitionistic fuzzy sets. They are instrumental in expressing and managing hesitant under uncertain environments, so they have been involved extensively in a diversity of scientific fields. This paper proposes a new Pythagorean entropy for Multi-Criteria Decision-Analysis (MCDA) problems. The entropy measures the fuzziness of two fuzzy sets and has an influential position in fuzzy functions. The more comprehensive the entropy, the more inadequate the ambiguity, so the decision-making established on entropy is beneficial. The COmplex PRoportional ASsessment (COPRAS) method is used to tackle uncertainty issues in MCDA and considers the singularity of one alternative over the rest of them. This can be enforced to maximize and minimize relevant criteria in an assessment where multiple opposing criteria are considered. Using the Pythagorean sets, we represent a decisional problem solution by using the COPRAS approach and the new Entropy measure. [ABSTRACT FROM AUTHOR]

This paper examines preferences across domains and contexts under conditions of risk and ambiguity and estimates the effect of attributes of the prospects on individual preferences. The main contribution of this paper is that it examines preferences using prospects with continuous distributions—a deviation from the widely used gambles with discrete probabilities. The argument put forward in this paper is that this design is at least as realistic of many real‐life situations and easier to comprehend. Data were obtained from field experiments where the tasks presented to subjects were framed as gain, loss and mixed and were not exclusively monetary. The findings show that risk preferences are context dependent, implying that the argument of risk‐taking being a stable personality trait is untenable. Risk (resp., ambiguity) preferences differ within and between domains. Subjects are risk‐avoiding and ambiguity avoiding in the gain domain and the reverse in the loss domain. An increase in the difference between the means of the smaller and larger variance prospects increases the preference for the larger variance prospect under risk but not under ambiguity. Stake orientation with regard to which ends of the prospects are bound at zero was crucial in subjects' decisions—an important finding not observed in discrete gamble experiments. [ABSTRACT FROM AUTHOR]

Strategic information system planning (SISP) is a central process that enables organizations to identify the strategic alignment of their IT portfolio to achieve their business needs and objectives. The extant SISP literature has focused on theoretical and processual aspects and has left methodological ambiguity about how SISP is practiced. This paper contributes to the current knowledge by providing a mixed-methods SISP framework labeled CSF-MCDM for company-wide strategic alignment. The paper conducts a methodological synthesis, embracing an expert-based qualitative approach based on a PEST-SWOT and causal layered analysis to draw the critical success factors of a next-generation business system for an automotive company in South Korea. The derived CSF dimensions and sub-criteria are evaluated by the multi-criteria decision-making model, engaging a strategy-as-practice lens to SISP to enable an integrative analysis of IS strategy formulation, planning, and implementation. The findings reveal the relative strategic priorities of dimensions, the following core activities, and the global priorities for resource distribution planning for IS strategy of the firm. This paper argues that bringing replicability with SISP and diversifying methodological approaches within the organization is substantial. This paper also suggests that future researchers validate the suggested framework for scientific replicability and expand the SISP research stream within the entire IS/IT ecosystem. [ABSTRACT FROM AUTHOR]

Although dysfunctional career decision-making beliefs represent an important assessment and intervention area in career counseling, the empirical foundation and the general mechanism of the dysfunctionality of dysfunctional career decision-making beliefs remain not fully clear. Based on the dual-process theory of career decision-making, the current study used a sample of U.S. college students (n = 200) and examined a longitudinal mediation model in which dysfunctional career decision-making beliefs predict subsequent career decidedness, career commitment, and academic major satisfaction through ambiguity aversion. The results supported the hypothesized mediation model in that dysfunctional career decision-making beliefs negatively predicted subsequent career decidedness, career commitment, and academic major satisfaction, and ambiguity aversion mediated all three links. Therefore, the present study not only shows that dysfunctional career decision-making has a pervasive detrimental role in career decision-making but also sheds light on the intricate relationship between dysfunctional career decision-making beliefs and ambiguity management in career decision-making. The limitations of this study and suggestions for future research are also discussed. [ABSTRACT FROM AUTHOR]

Decisions about one's health are often accompanied by uncertain outcomes, which may be either positively or negatively valenced. The presence of this uncertainty, which can range along a continuum from risk to ambiguity (i.e., decisions in which the outcome probabilities are known or unknown), can be perceived as threatening, and individuals tend to be averse to uncertain outcomes, attempting to avoid uncertainty when possible. We proposed that one way to reduce uncertainty aversion could be to provide opportunities to affirm one's core values, or "self‐affirmation." Prior research has suggested that self‐affirmation promotes health behavior by providing a buffer against potential threats to the self. However, the degree to which self‐affirmation affects decision making is still unclear. Across two studies, we tested the effects of a self‐affirmation manipulation on risk (Study 1) and ambiguity (Study 2) preferences for both potential gains and losses. In both studies, we found that, compared to the non‐affirmed group, affirmed individuals were more accepting of uncertainty when the decision involved potential gains, but not for potential losses. Furthermore, for risky decisions, the increased acceptance of uncertainty came at the expense of making choices consistent with the expected value, such that self‐affirmed individuals made more disadvantageous choices than non‐affirmed individuals. Our results suggest both benefits and costs of self‐affirmation in the context of risky choice, an important finding has given the many applications of self‐affirmation in behavioral decision‐making contexts. [ABSTRACT FROM AUTHOR]

The spherical fuzzy set (SFS) concept and its interval‐valued version (IVSFS) are among the recent developments aiming at handling the hesitancy representation issue in multiple attribute decision‐making problems. In SFS, decision‐makers can assign independent membership, non‐membership, and hesitancy degrees. IVSFS extends this feature by assigning intervals to these three degrees. In this manner, the uncertainty, vagueness, and ambiguity hidden in human judgements can be quantified and processed more comprehensively. In multiple attribute decision‐making problems, the attribute weights are not commonly known. To determine these weights, there are two families of methods: subjective and objective ones. While subjective methods need expert judgements in weighting, objective methods can reveal the weights from the current dataset. Entropy‐based weighting technique is one of the well‐known objective methods. In the study, two IVSFS entropy expressions are introduced, and their practicality is presented in obtaining objective weights. Then, an IVSFS extension of Additive Ratio Assessment Method is proposed and integrated with the entropy‐based weighting schema. The proposition is applied in solving a 3D printer selection problem and a comparative analysis is conducted to check its robustness and validity. [ABSTRACT FROM AUTHOR]